Carlson Nicholas A, Talmadge Michael S, Zaimes George G, Hawkins Troy R, Jiang Yuan
National Renewable Energy Laboratory, 15013 Denver West Parkway, Golden, Colorado 80401, United States.
Argonne National Laboratory, 9700 Cass Avenue, Lemont, Illinois 60439, United States.
Energy Fuels. 2024 Dec 19;39(1):444-453. doi: 10.1021/acs.energyfuels.4c03451. eCollection 2025 Jan 9.
The Co-Optimization of Fuels and Engines (Co-Optima) is a research and development consortia funded by the U.S. Department of Energy, which has engaged partners from national laboratories, universities, and industry to conduct multidisciplinary research at the intersection of biofuels and combustion sciences. Since 2016, the Co-Optima team has examined high-quality bioblendstocks, and their properties, as design variables for increasing efficiency in modern engines while decarbonizing on-road light- and heavy-duty vehicles. The objective of this analysis is to combine and expand upon research into Co-Optima multi-mode bioblendstocks, which blend with petroleum gasoline to form high efficiency fuels for combustion in both spark ignition and advanced compression ignition engines. Consequently, the economic and environmental impacts of deploying 10 different multi-mode bioblendstocks derived from renewable and circular resources are quantified. Each bioblendstock is evaluated across several variables including (1) target blend levels of 10, 20, and 30 vol %, (2) years from 2030 to 2050, (3) crude oil benchmark prices, (4) vehicle lifetime miles, and (5) incremental vehicle costs. A Monte Carlo simulator is developed using a refinery optimization model and life-cycle analysis tool from prior Co-Optima research to sample marginal abatement costs of CO, or cost of removing an additional unit of CO, corresponding to each bioblendstock while considering input variable uncertainties. Results show that the combination of efficiency gains from advanced multi-mode fuel-engine technologies and the reoptimization of refinery operations results in several bioblendstocks demonstrating near-zero expected marginal abatement costs. Variable importances are also explored to highlight which aspects of the multi-mode technology are most influential in determining marginal abatement costs. Results suggest that Co-Optima multi-mode technology could provide economically viable decarbonization contributions to electrification-resistant light-duty vehicle sectors or near-term emission reductions, while Co-Optima fuels or alternatives decarbonize further to reach net-zero status.
燃料与发动机协同优化(Co - Optima)是一个由美国能源部资助的研发联盟,它召集了来自国家实验室、大学和行业的合作伙伴,在生物燃料与燃烧科学的交叉领域开展多学科研究。自2016年以来,Co - Optima团队研究了高质量生物混合原料及其特性,将其作为设计变量,以提高现代发动机的效率,同时实现道路轻型和重型车辆的脱碳。本分析的目的是整合并扩展对Co - Optima多模式生物混合原料的研究,这些原料与石油汽油混合,形成用于火花点火发动机和先进压缩点火发动机燃烧的高效燃料。因此,对部署10种源自可再生和循环资源的不同多模式生物混合原料的经济和环境影响进行了量化。每种生物混合原料都根据几个变量进行评估,包括(1)10%、20%和30%体积的目标混合水平,(2)2030年至2050年的年份,(3)原油基准价格,(4)车辆使用寿命里程,以及(5)车辆增量成本。利用之前Co - Optima研究中的炼油厂优化模型和生命周期分析工具开发了一个蒙特卡洛模拟器,在考虑输入变量不确定性的同时,对每种生物混合原料对应的一氧化碳边际减排成本(即去除额外一单位一氧化碳的成本)进行采样。结果表明,先进的多模式燃料 - 发动机技术带来的效率提升与炼油厂运营的重新优化相结合,使得几种生物混合原料的预期边际减排成本接近零。还探讨了变量重要性,以突出多模式技术的哪些方面在确定边际减排成本方面最具影响力。结果表明,Co - Optima多模式技术可为抗电气化的轻型车辆部门提供经济上可行的脱碳贡献或近期减排,而Co - Optima燃料或替代方案则进一步脱碳以达到净零状态。